Low Power Phase Change Memory via Block Copolymer Self-assembly Technology

ABSTRACTWe report the demonstration of low power phase change memory (PCM) by forming thin self-assembled SiOx nanostructures between Ge2Sb2Te5 (GST) and a TiN heater layer utilizing a block copolymer (BCP) self-assembly technology. The reset current was decreased about three-fold as fill factor, which is the occupying area fraction of self-assembled SiOx nanostructures on a TiN heater layer, increased to 75.3%. The electro-thermal simulation shows the better heat efficiency due to the nano-patterned insulating oxide.

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Flexible One Diode-One Phase Change Memory Array Enabled by Block Copolymer Self-Assembly

ACS Nano ◽

10.1021/acsnano.5b00230 ◽

2015 ◽

Vol 9 (4) ◽

pp. 4120-4128 ◽

Cited By ~ 40

Author(s):

Beom Ho Mun ◽

Byoung Kuk You ◽

Se Ryeun Yang ◽

Hyeon Gyun Yoo ◽

Jong Min Kim ◽

...

Keyword(s):

Block Copolymer ◽

Phase Change ◽

Self Assembly ◽

Phase Change Memory ◽

Memory Array ◽

Change Memory

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Self-Assembled Incorporation of Modulated Block Copolymer Nanostructures in Phase-Change Memory for Switching Power Reduction

ACS Nano ◽

10.1021/nn4000176 ◽

2013 ◽

Vol 7 (3) ◽

pp. 2651-2658 ◽

Cited By ~ 55

Author(s):

Woon Ik Park ◽

Byoung Kuk You ◽

Beom Ho Mun ◽

Hyeon Kook Seo ◽

Jeong Yong Lee ◽

...

Keyword(s):

Block Copolymer ◽

Phase Change ◽

Phase Change Memory ◽

Power Reduction ◽

Switching Power ◽

Self Assembled ◽

Change Memory

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Si2Sb2Te6Phase Change Material for Low-Power Phase Change Memory Application

Applied Physics Express ◽

10.1143/apex.2.091401 ◽

2009 ◽

Vol 2 (9) ◽

pp. 091401 ◽

Cited By ~ 16

Author(s):

Xilin Zhou ◽

Liangcai Wu ◽

Zhitang Song ◽

Feng Rao ◽

Bo Liu ◽

...

Keyword(s):

Low Power ◽

Phase Change ◽

Phase Change Memory ◽

Change Material ◽

Change Memory

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R-Tree for phase change memory

Computer Science and Information Systems ◽

10.2298/csis160620008j ◽

2017 ◽

Vol 14 (2) ◽

pp. 347-367 ◽

Cited By ~ 2

Author(s):

Elkhan Jabarov ◽

Byung-Won On ◽

Gyu Choi ◽

Myong-Soon Park

Keyword(s):

Phase Change ◽

Spatial Data ◽

Processing Time ◽

Fill Factor ◽

Phase Change Memory ◽

Experimental Results ◽

Location Information ◽

Node Size ◽

Blank Node ◽

Change Memory

Nowadays, many applications use spatial data for instance-location information, so storing spatial data is important.We suggest using R -Tree over PCM. Our objective is to design a PCM-sensitive R -Tree that can store spatial data as well as improve the endurance problem. Initially, we examine how R -Tree causes endurance problems in PCM, and we then optimize it for PCM. We propose doubling the leaf node size, writing a split node to a blank node, updating parent nodes only once and not merging the nodes after deletion when the minimum fill factor requirement does not meet. Based on our experimental results while using benchmark dataset, the number of write operations to PCM in average decreased by 56 times by using the proposed R -Tree. Moreover, the proposed R -Tree scheme improves the performance in terms of processing time in average 23% compared to R -Tree.

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